Excessive aggregation of membrane proteins in the Martini model

Optimizing properties of translocation-enhancing transmembrane proteins

Cell membranes act as semi-permeable barriers, often restricting the entry of large or hydrophilic molecules. Nonetheless, certain amphiphilic molecules, such as antimicrobial and cell-penetrating peptides, can cross these barriers. In this study, we demonstrate that specific properties of transmembrane proteins/peptides can enhance membrane permeation of amphiphilic peptides. Using coarse-grained molecular dynamics with free-energy calculations, we identify key translocation-enhancing attributes of transmembrane proteins/peptides: a continuous hydrophilic patch, charged residues preferably in the membrane center, and aromatic hydrophobic residues. By employing both coarse-grained and atomistic simulations, complemented by experimental validation, we show that these properties not only enhance peptide translocation but also speed up lipid flip-flop. The enhanced flip-flop reinforces the idea that proteins such as scramblases and insertases not only share structural features but also operate through identical biophysical mechanisms enhancing the insertion and translocation of amphiphilic molecules. Our insights offer guidelines for the designing of translocation-enhancing proteins/peptides that could be used in medical and biotechnological applications.

Coarse-Grained Model of Glycosaminoglycans for Biomolecular Simulations

Proteoglycans contain glycosaminoglycans (GAGs) which are negatively charged linear polymers made of repeating disaccharide units of uronic acid and hexosamine units. They play vital roles in numerous physiological and pathological processes, particularly in governing cellular communication and attachment. Depending on their sulfonation state, acetylation, and glycosidic linkages, GAGs belong to different families. The high molecular weight, heterogeneity, and flexibility of GAGs hamper their characterization at atomic resolution, but this may be circumvented via coarse-grained (CG) approaches. In this work, we report a CG model for a library of common GAG types in their isolated or proteoglycan-linked states compatible with version 2.2 (v2.2) of the widely popular CG Martini force field. The model reproduces conformational and thermodynamic properties for a wide variety of GAGs, as well as matching structural and binding data for selected proteoglycan test systems. The parameters developed here may thus be employed to study a range of GAG-containing biomolecular systems, thereby benefiting from the efficiency and broad applicability of the Martini framework.

Improved Protein Dynamics and Hydration in the Martini3 Coarse-Grain Model

The Martini coarse-grain force-field has emerged as an important framework to probe cellular processes at experimentally relevant time- and length-scales. However, the recently developed version, the Martini3 force-field with the implemented Go̅ model (Martini3Go̅), as well as previous variants of the Martini model have not been benchmarked and rigorously tested for globular proteins. In this study, we consider three globular proteins, ubiquitin, lysozyme, and cofilin, and compare protein dynamics and hydration with observables from experiments and all-atom simulations. We show that the Martini3Go̅ model is able to accurately model the structural and dynamic features of small globular proteins. Overall, the structural integrity of the proteins is maintained, as validated by contact maps, radii of gyration (Rg), and SAXS profiles. The chemical shifts predicted from the ensemble sampled in the simulations are consistent with the experimental data. Further, a good match is observed in the protein-water interaction energetics, and the hydration levels of the residues are similar to atomistic simulations. However, the protein-water interaction dynamics is not accurately represented and appears to depend on the protein structural complexity, residue specificity, and water dynamics. Our work is a step toward testing and assessing the Martini3Go̅ model and provides insights into future efforts to refine Martini models with improved solvation effects and better correspondence to the underlying all-atom systems.

Multiscale Molecular Dynamics Simulations of the Homodimer Accessory Protein ORF7b of SARS-CoV-2

The SARS-CoV-2 ORF7b protein has drawn attention for its potential role in viral pathogenesis, but its structural details and lateral membrane associations remain elusive. In this study, we conducted multiscale molecular dynamics simulations to provide detailed molecular insights of the protein's dimerization, which is crucial for unraveling its structural model of protein-protein interface important to regulating cellular immune response. To gain a deeper understanding of homodimer configurations, we employed a machine learning algorithm for structural-based clustering. Clusters were categorized into three distinct groups for both parallel and antiparallel orientations, highlighting the influence of the initial monomer conformation on dimer configurations. Analysis of hydrogen bonding and π-π and π-cation stacking interactions within clusters revealed variations in interactions between clusters. In parallel dimers, weak stacking interactions in the transmembrane (TM) region were observed. In contrast, antiparallel dimers exhibited strong hydrogen bonding and stacking interactions contributing to tight dimeric packing, both within and outside the TM domain. Overall, our study provides a comprehensive view of the structural dynamics of ORF7b homodimerization in both parallel and antiparallel orientations. These findings shed light on the molecular interactions involved in ORF7b dimerization, which are crucial for understanding its potential roles in SARS-CoV-2 pathogenesis. This knowledge could inform future research and therapeutic strategies targeting this viral protein.

Molecular Dynamics Simulations in Protein-Protein Docking

Concerted interactions between all the cell components form the basis of biological processes. Protein-protein interactions (PPIs) constitute a tremendous part of this interaction network. Deeper insight into PPIs can help us better understand numerous diseases and lead to the development of new diagnostic and therapeutic strategies. PPI interfaces, until recently, were considered undruggable. However, it is now believed that the interfaces contain "hot spots," which could be targeted by small molecules. Such a strategy would require high-quality structural data of PPIs, which are difficult to obtain experimentally. Therefore, in silico modeling can complement or be an alternative to in vitro approaches. There are several computational methods for analyzing the structural data of the binding partners and modeling of the protein-protein dimer/oligomer structure. The major problem with in silico structure prediction of protein assemblies is obtaining sufficient sampling of protein dynamics. One of the methods that can take protein flexibility and the effects of the environment into account is Molecular Dynamics (MD). While sampling of the whole protein-protein association process with plain MD would be computationally expensive, there are several strategies to harness the method to PPI studies while maintaining reasonable use of resources. This chapter reviews known applications of MD in the PPI investigation workflows.

Palmitoylation modifies transmembrane adaptor protein PAG for ordered lipid environment: A molecular dynamics simulation study

We employed all-atom MD simulations to investigate the impact of palmitoylation on the PAG transmembrane peptide within various lipid environments, including the less explored boundary region separating lipid-ordered (Lo) and lipid-disordered (Ld) membrane phases. We found that palmitoylation of the peptide reduces its impact on membrane thickness, particularly within the Lo and boundary environments. Despite their hydrophobic nature, the palmitoyl chains on the peptide did not significantly affect the hydration of the surrounding membrane. Interestingly, the boundary membrane environment was found to be especially compatible with the palmitoylated peptide, suggesting its potential for accumulation in phase boundaries. Our findings highlight the importance of understanding how palmitoylation-modified peptides behave within membranes, with crucial implications for cell signaling and membrane organization. This knowledge may also inform the optimization of lipid membrane-based drug delivery systems, by improving our understanding of how drugs and excipients can be most effectively arranged within these carriers.

Improved Protein Model in SPICA Force Field

The previous version of the SPICA coarse-grained (CG) force field (FF) protein model focused primarily on membrane proteins and successfully reproduced the dimerization free energies of several transmembrane helices and the stable structures of various membrane protein assemblies. However, that model had limited accuracy when applied to other proteins, such as intrinsically disordered proteins (IDPs) and peripheral proteins, because the dimensions of the IDPs in an aqueous solution were too compact, and protein binding on the lipid membrane surface was overstabilized. To improve the accuracy of the SPICA FF model for the simulation of such systems, in this study, we introduce protein secondary structure-dependent nonbonded interaction parameters to the backbone segments and reoptimize almost all nonbonded parameters for amino acids. The improved FF proposed here successfully reproduces the radii of gyration of various IDPs, the binding sensitivity of several peripheral membrane proteins, and the dimerization free energies of several transmembrane helices. The new model also shows improved agreement with experiments on the free energy of peptide association in water. In addition, an extensive library of nonbonded interactions between proteins and lipids, including various glycerophospholipids, sphingolipids, and cholesterol, allows the study of specific interactions between lipids and peripheral and transmembrane proteins. Hence, the new SPICA FF (version 2) proposed herein is applicable with high accuracy for simulating a wide range of protein systems.

Phospholipids are imported into mitochondria by VDAC, a dimeric beta barrel scramblase

Mitochondria are double-membrane-bounded organelles that depend critically on phospholipids supplied by the endoplasmic reticulum. These lipids must cross the outer membrane to support mitochondrial function, but how they do this is unclear. We identify the Voltage Dependent Anion Channel (VDAC), an abundant outer membrane protein, as a scramblase-type lipid transporter that catalyzes lipid entry. On reconstitution into membrane vesicles, dimers of human VDAC1 and VDAC2 catalyze rapid transbilayer translocation of phospholipids by a mechanism that is unrelated to their channel activity. Coarse-grained molecular dynamics simulations of VDAC1 reveal that lipid scrambling occurs at a specific dimer interface where polar residues induce large water defects and bilayer thinning. The rate of phospholipid import into yeast mitochondria is an order of magnitude lower in the absence of VDAC homologs, indicating that VDACs provide the main pathway for lipid entry. Thus, VDAC isoforms, members of a superfamily of beta barrel proteins, moonlight as a class of phospholipid scramblases - distinct from alpha-helical scramblase proteins - that act to import lipids into mitochondria.

Dimerization mechanism of an inverted-topology ion channel in membranes

Many ion channels are multisubunit complexes where oligomerization is an obligatory requirement for function as the binding axis forms the charged permeation pathway. However, the mechanisms of in-membrane assembly of thermodynamically stable channels are largely unknown. Here, we demonstrate a key advance by reporting the dimerization equilibrium reaction of an inverted-topology, homodimeric fluoride channel Fluc in lipid bilayers. While the wild-type channel is a long-lived dimer, we leverage a known mutation, N43S, that weakens Na+ binding in a buried site at the interface, thereby unlocking the complex for reversible association in lipid bilayers. Single-channel recordings show that Na+ binding is required for fluoride conduction while single-molecule microscopy experiments demonstrate that N43S Fluc exists in a dynamic monomer-dimer equilibrium in the membrane, even following removal of Na+. Quantifying the thermodynamic stability while titrating Na+ indicates that dimerization occurs first, providing a membrane-embedded binding site where Na+ binding weakly stabilizes the complex. To understand how these subunits form stable assemblies while presenting charged surfaces to the membrane, we carried out molecular dynamics simulations, which show the formation of a thinned membrane defect around the exposed dimerization interface. In simulations where subunits are permitted to encounter each other while preventing protein contacts, we observe spontaneous and selective association at the native interface, where stability is achieved by mitigation of the membrane defect. These results suggest a model wherein membrane-associated forces drive channel assembly in the native orientation while subsequent factors, such as Na+ binding, result in channel activation.

Martini 3 Coarse-Grained Force Field for Cholesterol

Cholesterol plays a crucial role in biomembranes by regulating various properties, such as fluidity, rigidity, permeability, and organization of lipid bilayers. The latest version of the Martini model, Martini 3, offers significant improvements in interaction balance, molecular packing, and inclusion of new bead types and sizes. However, the release of the new model resulted in the need to reparameterize many core molecules, including cholesterol. Here, we describe the development and validation of a Martini 3 cholesterol model, addressing issues related to its bonded setup, shape, volume, and hydrophobicity. The proposed model mitigates some limitations of its Martini 2 predecessor while maintaining or improving the overall behavior.

Structural basis of dimerization of chemokine receptors CCR5 and CXCR4

G protein-coupled receptors (GPCRs) are prominent drug targets responsible for extracellular-to-intracellular signal transduction. GPCRs can form functional dimers that have been poorly characterized so far. Here, we show the dimerization mechanism of the chemokine receptors CCR5 and CXCR4 by means of an advanced free-energy technique named coarse-grained metadynamics. Our results reproduce binding events between the GPCRs occurring in the minute timescale, revealing a symmetric and an asymmetric dimeric structure for each of the three investigated systems, CCR5/CCR5, CXCR4/CXCR4, and CCR5/CXCR4. The transmembrane helices TM4-TM5 and TM6-TM7 are the preferred binding interfaces for CCR5 and CXCR4, respectively. The identified dimeric states differ in the access to the binding sites of the ligand and G protein, indicating that dimerization may represent a fine allosteric mechanism to regulate receptor activity. Our study offers structural basis for the design of ligands able to modulate the formation of CCR5 and CXCR4 dimers and in turn their activity, with therapeutic potential against HIV, cancer, and immune-inflammatory diseases.

The role of structural heterogeneity in the homodimerization of transmembrane proteins

The equilibrium association of transmembrane proteins plays a fundamental role in membrane protein function and cellular signaling. While the study of the equilibrium binding of single pass transmembrane proteins has received significant attention in experiment and simulation, the accurate assessment of equilibrium association constants remains a challenge to experiment and simulation. In experiment, there remain wide variations in association constants derived from experimental studies of the most widely studied transmembrane proteins. In simulation, state-of-the art methods have failed to adequately sample the thermodynamically relevant structures of the dimer state ensembles using coarse-grained models. In addition, all-atom force fields often fail to accurately assess the relative free energies of the dimer and monomer states. Given the importance of this fundamental biophysical process, it is essential to address these shortcomings. In this work, we establish an effective computational protocol for the calculation of equilibrium association constants for transmembrane homodimer formation. A set of transmembrane protein homodimers, used in the parameterization of the MARTINI v3 force field, are simulated using metadynamics, based on three collective variables. The method is found to be accurate and computationally efficient, providing a standard to be used in the future simulation studies using coarse-grained or all-atom models.

Understanding how transmembrane domains regulate interactions between human BST-2 and the SARS-CoV-2 accessory protein ORF7a

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of COVID, replicates at intracellular membranes. Bone marrow stromal antigen 2 (BST-2; tetherin) is an antiviral response protein that inhibits transport of viral particles after budding within infected cells. RNA viruses such as SARS-CoV-2 use various strategies to disable BST-2, including use of transmembrane 'accessory' proteins that interfere with BST-2 oligomerization. ORF7a is a small, transmembrane protein present in SARS-CoV-2 shown previously to alter BST-2 glycosylation and function. In this study, we investigated the structural basis for BST-2 ORF7a interactions, with a particular focus on transmembrane and juxtamembrane interactions. Our results indicate that transmembrane domains play an important role in BST-2 ORF7a interactions and mutations to the transmembrane domain of BST-2 can alter these interactions, particularly single-nucleotide polymorphisms in BST-2 that result in mutations such as I28S. Using molecular dynamics simulations, we identified specific interfaces and interactions between BST-2 and ORF7a to develop a structural basis for the transmembrane interactions. Differences in glycosylation are observed for BST-2 transmembrane mutants interacting with ORF7a, consistent with the idea that transmembrane domains play a key role in their heterooligomerization. Overall, our results indicate that ORF7a transmembrane domain interactions play a key role along with extracellular and juxtamembrane domains in modulating BST-2 function.

Theoretical and Data-Driven Approaches for Biomolecular Condensates

Biomolecular condensation processes are increasingly recognized as a fundamental mechanism that living cells use to organize biomolecules in time and space. These processes can lead to the formation of membraneless organelles that enable cells to perform distinct biochemical processes in controlled local environments, thereby supplying them with an additional degree of spatial control relative to that achieved by membrane-bound organelles. This fundamental importance of biomolecular condensation has motivated a quest to discover and understand the molecular mechanisms and determinants that drive and control this process. Within this molecular viewpoint, computational methods can provide a unique angle to studying biomolecular condensation processes by contributing the resolution and scale that are challenging to reach with experimental techniques alone. In this Review, we focus on three types of dry-lab approaches: theoretical methods, physics-driven simulations and data-driven machine learning methods. We review recent progress in using these tools for probing biomolecular condensation across all three fields and outline the key advantages and limitations of each of the approaches. We further discuss some of the key outstanding challenges that we foresee the community addressing next in order to develop a more complete picture of the molecular driving forces behind biomolecular condensation processes and their biological roles in health and disease.

Structures and membrane interactions of native serotonin transporter in complexes with psychostimulants

The serotonin transporter (SERT) is a member of the SLC6 neurotransmitter transporter family that mediates serotonin reuptake at presynaptic nerve terminals. SERT is the target of both therapeutic antidepressant drugs and psychostimulant substances such as cocaine and methamphetamines, which are small molecules that perturb normal serotonergic transmission by interfering with serotonin transport. Despite decades of studies, important functional aspects of SERT such as the oligomerization state of native SERT and its interactions with potential proteins remain unresolved. Here, we develop methods to isolate SERT from porcine brain (pSERT) using a mild, nonionic detergent, utilize fluorescence-detection size-exclusion chromatography to investigate its oligomerization state and interactions with other proteins, and employ single-particle cryo-electron microscopy to elucidate the structures of pSERT in complexes with methamphetamine or cocaine, providing structural insights into psychostimulant recognition and accompanying pSERT conformations. Methamphetamine and cocaine both bind to the central site, stabilizing the transporter in an outward open conformation. We also identify densities attributable to multiple cholesterol or cholesteryl hemisuccinate (CHS) molecules, as well as to a detergent molecule bound to the pSERT allosteric site. Under our conditions of isolation, we find that pSERT is best described as a monomeric entity, isolated without interacting proteins, and is ensconced by multiple cholesterol or CHS molecules.

Eukaryotic Cell Membranes: Structure, Composition, Research Methods and Computational Modelling

This paper deals with the problems encountered in the study of eukaryotic cell membranes. A discussion on the structure and composition of membranes, lateral heterogeneity of membranes, lipid raft formation, and involvement of actin and cytoskeleton networks in the maintenance of membrane structure is included. Modern methods for the study of membranes and their constituent domains are discussed. Various simplified models of biomembranes and lipid rafts are presented. Computer modelling is considered as one of the most important methods. This is stated that from the study of the plasma membrane structure, it is desirable to proceed to the diverse membranes of all organelles of the cell. The qualitative composition and molar content of individual classes of polar lipids, free sterols and proteins in each of these membranes must be considered. A program to create an open access electronic database including results obtained from the membrane modelling of individual cell organelles and the key sites of the membranes, as well as models of individual molecules composing the membranes, has been proposed.

Transmembrane dimers of type 1 receptors sample alternate configurations: MD simulations using coarse grain Martini 3 versus AlphaFold2 Multimer

Structures and dynamics of transmembrane (TM) receptor regions are key to understanding their signaling mechanism across membranes. Here we examine configurations of TM region dimers, assembled using the recent Martini 3 force field for coarse-grain (CG) molecular dynamics simulations. At first glance, our results show only a reasonable agreement with ab initio predictions using PREDDIMER and AlphaFold2 Multimer and with nuclear magnetic resonance (NMR)-derived structures. 5 of 11 CG TM structures are similar to the NMR structures (within <3.5 Å root-mean-square deviation [RMSD]) compared with 10 and 9 using PREDDIMER and AlphaFold2, respectively (with 8 structures of the later within 1.5 Å). Surprisingly, AlphaFold2 predictions are closer to NMR structures when the 2001 instead of 2020 database is used for training. The CG simulations reveal that alternative configurations of TM dimers readily interconvert with a predominant population. The implications for transmembrane signaling are discussed, including for the development of peptide-based pharmaceuticals.

Tyrosine kinases compete for growth hormone receptor binding and regulate receptor mobility and degradation

Growth hormone (GH) acts via JAK2 and LYN to regulate growth, metabolism, and neural function. However, the relationship between these tyrosine kinases remains enigmatic. Through an interdisciplinary approach combining cell biology, structural biology, computation, and single-particle tracking on live cells, we find overlapping LYN and JAK2 Box1-Box2-binding regions in GH receptor (GHR). Our data implicate direct competition between JAK2 and LYN for GHR binding and imply divergent signaling profiles. We show that GHR exhibits distinct mobility states within the cell membrane and that activation of LYN by GH mediates GHR immobilization, thereby initiating its nanoclustering in the membrane. Importantly, we observe that LYN mediates cytokine receptor degradation, thereby controlling receptor turnover and activity, and this applies to related cytokine receptors. Our study offers insight into the molecular interactions of LYN with GHR and highlights important functions for LYN in regulating GHR nanoclustering, signaling, and degradation, traits broadly relevant to many cytokine receptors.

Effective Molecular Dynamics from Neural Network-Based Structure Prediction Models

Recent breakthroughs in neural network-based structure prediction methods, such as AlphaFold2 and RoseTTAFold, have dramatically improved the quality of computational protein structure prediction. These models also provide statistical confidence scores that can estimate uncertainties in the predicted structures, but it remains unclear to what extent these scores are related to the intrinsic conformational dynamics of proteins. Here, we compare AlphaFold2 prediction scores with explicit large-scale molecular dynamics simulations of 28 one- and two-domain proteins with varying degrees of flexibility. We demonstrate a strong correlation between the statistical prediction scores and the explicit motion derived from extensive atomistic molecular dynamics simulations and further derive an elastic network model based on the statistical scores of AlphFold2 (AF-ENM), which we benchmark in combination with coarse-grained molecular dynamics simulations. We show that our AF-ENM method reproduces the global protein dynamics with improved accuracy, providing a powerful way to derive effective molecular dynamics using neural network-based structure prediction models.

A top-down and bottom-up combined strategy for parameterization of coarse-grained force fields for phospholipids

Coarse-graining (CG) molecular dynamics (MD) simulations are widely used in interpreting experimental observations and predicting assembly morphology as well as collective behaviour but also face the problem of poor accuracy. A main issue is that cross-termed interactions between different CG beads are inadequately parameterized. This work proposes a novel top-down and bottom-up combined strategy to parameterize both self- and cross-termed interactions of zwitterionic phospholipids in water solution based on a piecewise Morse potential describing nonbonded van der Waals interactions. The self-interacting force parameters were optimized by matching experimental density, heat vapourization, and surface tension in a top-down manner, while the cross-termed interactions were optimized by fitting pseudo properties obtained from atomistic simulations in a bottom-up way, including mixing density, intermolecular energy, and radial mixing coefficient. The transferability of the CG force field (FF) was confirmed by reproducing a variety of structural and thermodynamic properties of lipid membranes in both liquid and gel phases. This FF can well depict vesicle self-assembly and vesicle fusion processes. Matching pseudo properties opens a new way to develop CG FF with increased accuracy and transferability.

Scaling Protein-Water Interactions in the Martini 3 Coarse-Grained Force Field to Simulate Transmembrane Helix Dimers in Different Lipid Environments

Martini 3, the latest version of the widely used Martini force field for coarse-grained molecular dynamics simulations, is a promising tool to investigate proteins in phospholipid bilayers. However, simulating other lipid environments, such as detergent micelles, presents challenges due to the absence of validated parameters for their constituent molecules. Here, we propose parameters for the micelle-forming surfactant, dodecylphosphocholine (DPC). These result in micelle assembly with aggregation numbers in agreement with the experimental values. However, we identified a lack of hydrophobic interactions between transmembrane helix protein dimers and the tails of DPC molecules, preventing insertion and stabilization of the protein in the micelles. This problem was also observed for protein insertion by self-assembling 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC) or dipalmitoylphosphatidylcholine (DPPC) bilayers. We propose the reduction of the nonbonded interactions between protein and water beads by 10% as a simple and effective solution to this problem that enables protein encapsulation in phospholipid micelles and bilayers without altering protein dimerization or the bilayer structure.

Dimerization mechanism of an inverted-topology ion channel in membranes

Many ion channels are multi-subunit complexes with a polar permeation pathway at the oligomeric interface, but their mechanisms of assembly into functional, thermodynamically stable units within the membrane are largely unknown. Here we characterize the assembly of the inverted-topology, homodimeric fluoride channel Fluc, leveraging a known mutation, N43S, that weakens Na + binding to the dimer interface, thereby unlocking the complex. While single-channel recordings show Na + is required for activation, single-molecule photobleaching and bulk Förster Resonance Energy Transfer experiments in lipid bilayers demonstrate that N43S Fluc monomers and dimers exist in dynamic equilibrium, even without Na + . Molecular dynamics simulations indicate this equilibrium is dominated by a differential in the lipid-solvation energetics of monomer and dimer, which stems from hydrophobic exposure of the polar ion pathway in the monomer. These results suggest a model wherein membrane-associated forces induce channel assembly while subsequent factors, in this case Na + binding, result in channel activation.

Teaser

Membrane morphology energetics foster inverted-topology Fluc channels to form dimers, which then become active upon Na + binding.

The impact of bilayer composition on the dimerization properties of the Slg1 stress sensor TMD from a multiscale analysis

The impact of mutual interactions between the transmembrane domains of membrane proteins and lipids on bilayer properties has gained major attraction. Most simulation studies of membranes rely on the Martini force field, which has proven extremely helpful in providing molecular insights into realistic systems. Accordingly, an evaluation of the accuracy of the Martini force field is crucial to be able to correctly interpret the reported data. In this study, we combine atomistic and coarse-grained Martini simulations to investigate the properties of transmembrane domains (TMDs) in a model yeast membrane. The results show that the TMD binding state (monomeric and dimeric with positive or negative crossing angle) and the membrane composition significantly influence the properties around the TMDs and change TMD-TMD and TMD-lipid affinities. Furthermore, ergosterol (ERG) exhibits a strong affinity to TMD dimers. Importantly, the right-handed TMD dimer configuration is stabilized via TMD-TMD contacts by the addition of asymmetric anionic phosphatidylserine (PS). The coarse-grained simulations corroborate many of these findings, with two notable exceptions: a systematic overestimation of TMD-ERG interaction and lack of stabilization of the right-handed TMD dimers with the addition of PS.

Molecular Dynamics Simulations of Self-Assembling Colloids in Fed-State Human Intestinal Fluids and Their Solubilization of Lipophilic Drugs

Bioavailability of oral drugs often depends on how soluble the active pharmaceutical ingredient is in the fluid present in the small intestine. For efficient drug discovery and development, computational tools are needed for estimating this drug solubility. In this paper, we examined human intestinal fluids collected in the fed state, with coarse-grained molecular dynamics simulations. The experimentally obtained concentrations in aspirated duodenal fluids from five healthy individuals were used in three simulation sets to evaluate the importance of the initial distribution of molecules and the presence of glycerides in the simulation box when simulating the colloidal environment of the human intestinal fluid. We observed self-assembly of colloidal structures of different types: prolate, elongated, and oblate micelles, and vesicles. Glycerides were important for the formation of vesicles, and their absence was shown to induce elongated micelles. We then simulated the impact of digestion and absorption on the different colloidal types. Finally, we looked at the solubilization of three model compounds of increasing lipophilicity (prednisolone, fenofibrate, and probucol) by calculating contact ratios of drug-colloid to drug-water. Our simulation results of colloidal interactions with APIs were in line with experimental solubilization data but showed a dissimilarity to solubility values when comparing fasted-/fed-state ratios between two of the APIs. This work shows that coarse-grained molecular dynamics simulation is a promising tool for investigation of the intestinal fluids, in terms of colloidal attributes and drug solubility.

Probing effects of the SARS-CoV-2 E protein on membrane curvature and intracellular calcium

SARS-CoV-2 contains four structural proteins in its genome. These proteins aid in the assembly and budding of new virions at the ER-Golgi intermediate compartment (ERGIC). Current fundamental research efforts largely focus on one of these proteins – the spike (S) protein. Since successful antiviral therapies are likely to target multiple viral components, there is considerable interest in understanding the biophysical role of its other structural proteins, in particular structural membrane proteins. Here, we have focused our efforts on the characterization of the full-length envelope (E) protein from SARS-CoV-2, combining experimental and computational approaches. Recombinant expression of the full-length E protein from SARS-CoV-2 reveals that this membrane protein is capable of independent multimerization, possibly as a tetrameric or smaller species. Fluorescence microscopy shows that the protein localizes intracellularly, and coarse-grained MD simulations indicate it causes bending of the surrounding lipid bilayer, corroborating a potential role for the E protein in viral budding. Although we did not find robust electrophysiological evidence of ion-channel activity, cells transfected with the E protein exhibited reduced intracellular Ca²⁺, which may further promote viral replication. However, our atomistic MD simulations revealed that previous NMR structures are relatively unstable, and result in models incapable of ion conduction. Our study highlights the importance of using high-resolution structural data obtained from a full-length protein to gain detailed molecular insights, and eventually permitting virtual drug screening.

Unraveling membrane properties at the organelle-level with LipidDyn

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Lipidomics of organelles could be used to design models for molecular simulations.

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The bottleneck is the analysis and rationalization of the data from simulations.

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LipidDyn is an automated pipeline to streamline the analyses of lipid bilayers.

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LipidDyn allows to collect analysis in a non-time-consuming and reproducible manner.

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We applied LipidDyn to different case studies to illustrate its potential.

Cellular membranes are formed from different lipids in various amounts and proportions depending on the subcellular localization. The lipid composition of membranes is sensitive to changes in the cellular environment, and its alterations are linked to several diseases. Lipids not only form lipid-lipid interactions but also interact with other biomolecules, including proteins.

Molecular dynamics (MD) simulations are a powerful tool to study the properties of cellular membranes and membrane-protein interactions on different timescales and resolutions. Over the last few years, software and hardware for biomolecular simulations have been optimized to routinely run long simulations of large and complex biological systems. On the other hand, high-throughput techniques based on lipidomics provide accurate estimates of the composition of cellular membranes at the level of subcellular compartments. Lipidomic data can be analyzed to design biologically relevant models of membranes for MD simulations. Similar applications easily result in a massive amount of simulation data where the bottleneck becomes the analysis of the data. In this context, we developed LipidDyn, a Python-based pipeline to streamline the analyses of MD simulations of membranes of different compositions. Once the simulations are collected, LipidDyn provides average properties and time series for several membrane properties such as area per lipid, thickness, order parameters, diffusion motions, lipid density, and lipid enrichment/depletion. The calculations exploit parallelization, and the pipeline includes graphical outputs in a publication-ready form. We applied LipidDyn to different case studies to illustrate its potential, including membranes from cellular compartments and transmembrane protein domains. LipidDyn is available free of charge under the GNU General Public License from https://github.com/ELELAB/LipidDyn.

Finite-Size Effects in Simulations of Peptide/Lipid Assembly

Abstract

Molecular dynamics simulations are an attractive tool for understanding lipid/peptide self-assembly but can be plagued by inaccuracies when the system sizes are too small. The general guidance from self-assembly simulations of homogeneous micelles is that the total number of surfactants should be three to five times greater than the equilibrium aggregate number of surfactants per micelle. Herein, the heuristic is tested on the more complicated self-assembly of lipids and amphipathic peptides using the Cooke and Martini 3 coarse-grained models. Cooke model simulations with 50 to 1000 lipids and no peptide are dominated by finite-size effects, with usually one aggregate (micelle or nanodisc) containing most of the lipids forming at each system size. Approximately 200 systems of different peptide/lipid (P/L) ratios and sizes of up to 1000 lipids yield a “finite-size phase diagram” for peptide driven self-assembly, including a coexistence region of micelles and discs. Insights from the Cooke model are applied to the assembly of dimyristoylphosphatidylcholine and the ELK-neutral peptide using the Martini 3 model. Systems of 150, 450, and 900 lipids with P/L = 1/6.25 form mixtures of lipid-rich discs that agree in size with experiment and peptide-rich micelles. Only the 150-lipid system shows finite-size effects, which arise from the long-tailed distribution of aggregate sizes. The general rule of three to five times the equilibrium aggregate size remains a practical heuristic for the Cooke and Martini 3 systems investigated here.

Graphical Abstract

Supplementary Information

The online version contains supplementary material available at 10.1007/s00232-022-00255-9.

Computational and Experimental Evaluation of the Stability of a GLP-1-like Peptide in Ethanol–Water Mixtures

Aggregation resulting from the self-association of peptide molecules remains a major challenge during preformulation. Whereas certain organic solvents are known to promote aggregation, ethanol (EtOH) is capable of disrupting interactions between peptide molecules. It is unclear whether it is beneficial or counterproductive to include EtOH in formulations of short peptides. Here, we employed molecular dynamics simulations using the DAFT protocol and MARTINI force field to predict the formation of self-associated dimers and to estimate the stability of a GLP-1-like peptide (G48) in 0–80% aqueous EtOH solutions. Both simulation and experimental data reveal that EtOH leads to a remarkable increase in the conformational stability of the peptide when stored over 15 days at 27 °C. In the absence of EtOH, dimerisation and subsequent loss in conformational stability (α-helix → random coil) were observed. EtOH improved conformational stability by reducing peptide–peptide interactions. The data suggest that a more nuanced approach may be applied in formulation decision making and, if the native state of the peptide is an α-helix organic solvent, such as EtOH, may enhance stability and improve prospects of long-term storage.

Characterization of the membrane interactions of phospholipase Cγ reveals key features of the active enzyme

PLCγ enzymes are autoinhibited in resting cells and form key components of intracellular signaling that are also linked to disease development. Insights into physiological and aberrant activation of PLCγ require understanding of an active, membrane-bound form, which can hydrolyze inositol-lipid substrates. Here, we demonstrate that PLCγ1 cannot bind membranes unless the autoinhibition is disrupted. Through extensive molecular dynamics simulations and experimental evidence, we characterize membrane binding by the catalytic core domains and reveal previously unknown sites of lipid interaction. The identified sites act in synergy, overlap with autoinhibitory interfaces, and are shown to be critical for the phospholipase activity in cells. This work provides direct evidence that PLCγ1 is inhibited through obstruction of its membrane-binding surfaces by the regulatory region and that activation must shift PLCγ1 to a conformation competent for membrane binding. Knowledge of the critical sites of membrane interaction extends the mechanistic framework for activation, dysregulation, and therapeutic intervention.

On Computing Equilibrium Binding Constants for Protein-Protein Association in Membranes

Protein association in lipid membranes is fundamental to membrane protein function and of great biomedical relevance. All-atom and coarse-grained models have been extensively used to understand the protein-protein interactions in the membrane and to compute equilibrium association constants. However, slow translational and rotational diffusion of protein in membrane presents challenges to the effective sampling of conformations defining the ensembles of free and bound states contributing to the association equilibrium and the free energy of dimerization. We revisit the homodimerization equilibrium of the TM region of glycophorin A. Conformational sampling is performed using umbrella sampling along previously proposed one-dimensional collective variables and compared with sampling over a two-dimensional collective variable space using the MARTINI v2.2 force field. We demonstrate that the one-dimensional collective variables suffer from restricted sampling of the native homodimer conformations leading to a biased free energy landscape. Conversely, simulations along the two-dimensional collective variable effectively characterize the thermodynamically relevant native and non-native interactions contributing to the association equilibrium. These results demonstrate the challenges associated with accurately characterizing binding equilibria when multiple poses contribute to the bound state ensemble.

AI-based structure prediction empowers integrative structural analysis of human nuclear pores

INTRODUCTION The eukaryotic nucleus pro-tects the genome and is enclosed by the two membranes of the nuclear envelope. Nuclear pore complexes (NPCs) perforate the nuclear envelope to facilitate nucleocytoplasmic transport. With a molecular weight of ∼120 MDa, the human NPC is one of the larg-est protein complexes. Its ~1000 proteins are taken in multiple copies from a set of about 30 distinct nucleoporins (NUPs). They can be roughly categorized into two classes. Scaf-fold NUPs contain folded domains and form a cylindrical scaffold architecture around a central channel. Intrinsically disordered NUPs line the scaffold and extend into the central channel, where they interact with cargo complexes. The NPC architecture is highly dynamic. It responds to changes in nuclear envelope tension with conforma-tional breathing that manifests in dilation and constriction movements. Elucidating the scaffold architecture, ultimately at atomic resolution, will be important for gaining a more precise understanding of NPC function and dynamics but imposes a substantial chal-lenge for structural biologists. RATIONALE Considerable progress has been made toward this goal by a joint effort in the field. A synergistic combination of complementary approaches has turned out to be critical. In situ structural biology techniques were used to reveal the overall layout of the NPC scaffold that defines the spatial reference for molecular modeling. High-resolution structures of many NUPs were determined in vitro. Proteomic analysis and extensive biochemical work unraveled the interaction network of NUPs. Integra-tive modeling has been used to combine the different types of data, resulting in a rough outline of the NPC scaffold. Previous struc-tural models of the human NPC, however, were patchy and limited in accuracy owing to several challenges: (i) Many of the high-resolution structures of individual NUPs have been solved from distantly related species and, consequently, do not comprehensively cover their human counterparts. (ii) The scaf-fold is interconnected by a set of intrinsically disordered linker NUPs that are not straight-forwardly accessible to common structural biology techniques. (iii) The NPC scaffold intimately embraces the fused inner and outer nuclear membranes in a distinctive topol-ogy and cannot be studied in isolation. (iv) The conformational dynamics of scaffold NUPs limits the resolution achievable in structure determination. RESULTS In this study, we used artificial intelligence (AI)-based prediction to generate an exten-sive repertoire of structural models of human NUPs and their subcomplexes. The resulting models cover various domains and interfaces that so far remained structurally uncharac-terized. Benchmarking against previous and unpublished x-ray and cryo-electron micros-copy structures revealed unprecedented accu-racy. We obtained well-resolved cryo-electron tomographic maps of both the constricted and dilated conformational states of the hu-man NPC. Using integrative modeling, we fit-ted the structural models of individual NUPs into the cryo-electron microscopy maps. We explicitly included several linker NUPs and traced their trajectory through the NPC scaf-fold. We elucidated in great detail how mem-brane-associated and transmembrane NUPs are distributed across the fusion topology of both nuclear membranes. The resulting architectural model increases the structural coverage of the human NPC scaffold by about twofold. We extensively validated our model against both earlier and new experimental data. The completeness of our model has enabled microsecond-long coarse-grained molecular dynamics simulations of the NPC scaffold within an explicit membrane en-vironment and solvent. These simulations reveal that the NPC scaffold prevents the constriction of the otherwise stable double-membrane fusion pore to small diameters in the absence of membrane tension. CONCLUSION Our 70-MDa atomically re-solved model covers >90% of the human NPC scaffold. It captures conforma-tional changes that occur during dilation and constriction. It also reveals the precise anchoring sites for intrinsically disordered NUPs, the identification of which is a prerequisite for a complete and dy-namic model of the NPC. Our study exempli-fies how AI-based structure prediction may accelerate the elucidation of subcellular ar-chitecture at atomic resolution. [Figure: see text].

Specific interactions of peripheral membrane proteins with lipids: what can molecular simulations show us?

Peripheral membrane proteins (PMPs) can reversibly and specifically bind to biological membranes to carry out functions such as cell signalling, enzymatic activity, or membrane remodelling. Structures of these proteins and of their lipid-binding domains are typically solved in a soluble form, sometimes with a lipid or lipid headgroup at the binding site. To provide a detailed molecular view of PMP interactions with the membrane, computational methods such as molecular dynamics (MD) simulations can be applied. Here, we outline recent attempts to characterise these binding interactions, focusing on both intracellular proteins, such as phosphatidylinositol phosphate (PIP)-binding domains, and extracellular proteins such as glycolipid-binding bacterial exotoxins. We compare methods used to identify and analyse lipid-binding sites from simulation data and highlight recent work characterising the energetics of these interactions using free energy calculations. We describe how improvements in methodologies and computing power will help MD simulations to continue to contribute to this field in the future.

Lipid-Mediated Association of the Slg1 Transmembrane Domains in Yeast Plasma Membranes

Clustering of transmembrane proteins underlies a multitude of fundamental biological processes at the plasma membrane (PM) such as receptor activation, lateral domain formation, and mechanotransduction. The self-association of the respective transmembrane domains (TMDs) has also been suggested to be responsible for the micron-scaled patterns seen for integral membrane proteins in the budding yeast PM. However, the underlying interplay between the local lipid composition and the TMD identity is still not mechanistically understood. In this work, we combined coarse-grained molecular dynamics simulations of simplified bilayer systems with high-resolution live-cell microscopy to analyze the distribution of a representative helical yeast TMD from the PM sensor Slg1 within different lipid environments. In our simulations, we specifically evaluated the effects of acyl chain saturation and anionic lipid head groups on the association of two TMDs. We found that weak lipid-protein interactions significantly affect the configuration of TMD dimers and the free energy of association. Increased amounts of unsaturated phospholipids (PLs) strongly reduced the helix-helix interaction, while the presence of anionic phosphatidylserine (PS) hardly affected the dimer formation. We could experimentally confirm this surprising lack of effect of PS using the network factor, a mesoscopic measure of PM pattern formation in yeast cells. Simulations also showed that the formation of TMD dimers in turn increased the order parameter of the surrounding lipids and induced long-range perturbations in lipid organization. In summary, our results shed new light on the mechanisms of lipid-mediated dimerization of TMDs in complex lipid mixtures.

SPICA Force Field for Proteins and Peptides

A coarse-grained (CG) model for peptides and proteins was developed as an extension of the Surface Property fItting Coarse grAined (SPICA) force field (FF). The model was designed to examine membrane proteins that are fully compatible with the lipid membranes of the SPICA FF. A preliminary version of this protein model was created using thermodynamic properties, including the surface tension and density in the SPICA (formerly called SDK) FF. In this study, we improved the CG protein model to facilitate molecular dynamics (MD) simulations with a reproduction of multiple properties from both experiments and all-atom (AA) simulations. An elastic network model was adopted to maintain the secondary structure within a single chain. The side-chain analogues reproduced the transfer free energy profiles across the lipid membrane and demonstrated reasonable association free energy (potential of mean force) in water compared to those from AA MD. A series of peptides/proteins adsorbed onto or penetrated into the membrane simulated by the CG MD correctly predicted the penetration depths and tilt angles of peripheral and transmembrane peptides/proteins as comparable to those in the orientations of proteins in membranes (OPM) database. In addition, the dimerization free energies of several transmembrane helices within a lipid bilayer were comparable to those from experimental estimation. Application studies on a series of membrane protein assemblies, scramblases, and poliovirus capsids demonstrated the good performance of the SPICA FF.

Investigation of the pH-dependent aggregation mechanisms of GCSF using low resolution protein characterization techniques and advanced molecular dynamics simulations

Granulocyte-colony stimulating factor (GCSF) is a widely used therapeutic protein to treat neutropenia. GCSF has an increased propensity to aggregate if the pH is increased above 5.0. Although GCSF is very well experimentally characterized, the exact pH-dependent aggregation mechanism of GCSF is still under debate. This study aimed to model the complex pH-dependent aggregation behavior of GCSF using state-of-the-art simulation techniques. The conformational stability of GCSF was investigated by performing metadynamics simulations, while the protein-protein interactions were investigated using coarse-grained (CG) simulations of multiple GCSF monomers. The CG simulations were directly compared with small-angle X-ray (SAXS) data. The metadynamics simulations demonstrated that the orientations of Trp residues in GCSF are dependent on pH. The conformational change of Trp residues is due to the loss of Trp-His interactions at the physiological pH, which in turn may increase protein flexibility. The helical structure of GCSF was not affected by the pH conditions of the simulations. Our CG simulations indicate that at pH 4.0, the colloidal stability may be more important than the conformational stability of GCSF. The electrostatic potential surface and CG simulations suggested that the basic residues are mainly responsible for colloidal stability as deprotonation of these residues causes a reduction of the highly positively charged electrostatic barrier close to the aggregation-prone long loop regions.

Assembly and Analysis of Cell-Scale Membrane Envelopes

The march toward exascale computing will enable routine molecular simulation of larger and more complex systems, for example, simulation of entire viral particles, on the scale of approximately billions of atoms─a simulation size commensurate with a small bacterial cell. Anticipating the future hardware capabilities that will enable this type of research and paralleling advances in experimental structural biology, efforts are currently underway to develop software tools, procedures, and workflows for constructing cell-scale structures. Herein, we describe our efforts in developing and implementing an efficient and robust workflow for construction of cell-scale membrane envelopes and embedding membrane proteins into them. A new approach for construction of massive membrane structures that are stable during the simulations is built on implementing a subtractive assembly technique coupled with the development of a structure concatenation tool (fastmerge), which eliminates overlapping elements based on volumetric criteria rather than adding successive molecules to the simulation system. Using this approach, we have constructed two "protocells" consisting of MARTINI coarse-grained beads to represent cellular membranes, one the size of a cellular organelle and another the size of a small bacterial cell. The membrane envelopes constructed here remain whole during the molecular dynamics simulations performed and exhibit water flux only through specific proteins, demonstrating the success of our methodology in creating tight cell-like membrane compartments. Extended simulations of these cell-scale structures highlight the propensity for nonspecific interactions between adjacent membrane proteins leading to the formation of protein microclusters on the cell surface, an insight uniquely enabled by the scale of the simulations. We anticipate that the experiences and best practices presented here will form the basis for the next generation of cell-scale models, which will begin to address the addition of soluble proteins, nucleic acids, and small molecules essential to the function of a cell.

Gecko adhesion: a molecular-simulation perspective on the effect of humidity

Gecko adhesion is investigated by molecular dynamics simulations. It is known, that the gecko adhesion system shows increased pull-off forces in humid environments. A coarse-grained model of gecko beta keratin, previously developed in our group, is extended and used to elucidate the molecular mechanisms involved in this humidity effect on adhesion. We show that neither the change of the elastic properties of gecko keratin, nor capillary forces, can solely explain the increased pull-off forces of wet gecko keratin. Instead, we establish a molecular picture of gecko adhesion where the interplay between capillary bridges and a mediator effect of water, enhances pull-off forces, consistent with observations in AFM experiments at high humidities. We find that water density is raised locally, in molecular scale asperities of the gecko keratin and that this increase in local water density smoothes the surface-spatula interface. Water, which is absorbed into the keratin, acts as a mediator, and leads during pull-off to the dominant contribution in the van der Waals energy, because the dispersion interactions between water and surface are primarily opposing the pull-off.

Protein dynamics and lipid affinity of monomeric, zeaxanthin-binding LHCII in thylakoid membranes

The xanthophyll cycle in the antenna of photosynthetic organisms under light stress is one of the most well-known processes in photosynthesis, but its role is not well understood. In the xanthophyll cycle, violaxanthin (Vio) is reversibly transformed to zeaxanthin (Zea) that occupies Vio binding sites of light-harvesting antenna proteins. Higher monomer/trimer ratios of the most abundant light-harvesting protein, the light-harvesting complex II (LHCII), usually occur in Zea accumulating membranes and have been observed in plants after prolonged illumination and during high-light acclimation. We present a combined NMR and coarse-grained simulation study on monomeric LHCII from the npq2 mutant that constitutively binds Zea in the Vio binding pocket. LHCII was isolated from ¹³C-enriched npq2 Chlamydomonas reinhardtii (Cr) cells and reconstituted in thylakoid lipid membranes. NMR results reveal selective changes in the fold and dynamics of npq2 LHCII compared with the trimeric, wild-type and show that npq2 LHCII contains multiple mono- or digalactosyl diacylglycerol lipids (MGDG and DGDG) that are strongly protein bound. Coarse-grained simulations on npq2 LHCII embedded in a thylakoid lipid membrane agree with these observations. The simulations show that LHCII monomers have more extensive lipid contacts than LHCII trimers and that protein-lipid contacts are influenced by Zea. We propose that both monomerization and Zea binding could have a functional role in modulating membrane fluidity and influence the aggregation and conformational dynamics of LHCII with a likely impact on photoprotection ability.

Computational Models for the Study of Protein Aggregation

Protein aggregation has been studied by many groups around the world for many years because it can be the cause of a number of neurodegenerative diseases that have no effective treatment. Obtaining the structure of related fibrils and toxic oligomers, as well as describing the pathways and main factors that govern the self-organization process, is of paramount importance, but it is also very difficult. To solve this problem, experimental and computational methods are often combined to get the most out of each method. The effectiveness of the computational approach largely depends on the construction of a reasonable molecular model. Here we discussed different versions of the four most popular all-atom force fields AMBER, CHARMM, GROMOS, and OPLS, which have been developed for folded and intrinsically disordered proteins, or both. Continuous and discrete coarse-grained models, which were mainly used to study the kinetics of aggregation, are also summarized.

Improved Parameterization of Phosphatidylinositide Lipid Headgroups for the Martini 3 Coarse-Grain Force Field

Phosphoinositides are a family of membrane phospholipids that play crucial roles in membrane regulatory events. As such, these lipids are often a key part of molecular dynamics simulation studies of biological membranes, in particular of those employing coarse-grain models because of the potential long times and sizes of the involved membrane processes. Version 3 of the widely used Martini coarse-grain force field has been recently published, greatly refining many aspects of biomolecular interactions. In order to properly use it for lipid membrane simulations with phosphoinositides, we put forth the Martini 3-specific parameterization of inositol, phosphatidylinositol, and seven physiologically relevant phosphorylated derivatives of phosphatidylinositol. Compared to parameterizations for earlier Martini versions, focus was put on a more accurate reproduction of the behavior seen in both atomistic simulations and experimental studies, including the signaling-relevant phosphoinositide interaction with divalent cations. The models that we develop improve upon the conformational dynamics of phosphoinositides in the Martini force field and provide stable topologies at typical Martini time steps. They are able to reproduce experimentally known protein-binding poses as well as phosphoinositide aggregation tendencies. The latter was tested both in the presence and absence of calcium and included correct behavior of PI(4,5)P₂ calcium-induced clusters, which can be of relevance for regulation.

Modulation of adenosine A2a receptor oligomerization by receptor activation and PIP2 interactions

GPCRs have been shown to form oligomers, which generate distinctive signaling outcomes. However, the structural nature of the oligomerization process remains uncertain. We have characterized oligomeric configurations of the adenosine A2a receptor (A2aR) by combining large-scale molecular dynamics simulations with Markov state models. These oligomeric structures may also serve as templates for studying oligomerization of other class A GPCRs. Our simulation data revealed that receptor activation results in enhanced oligomerization, more diverse oligomer populations, and a more connected oligomerization network. The active state conformation of the A2aR shifts protein-protein association interfaces to those involving intracellular loop ICL3 and transmembrane helix TM6. Binding of PIP₂ to A2aR stabilizes protein-protein interactions via PIP₂-mediated association interfaces. These results indicate that A2aR oligomerization is responsive to the local membrane lipid environment. This, in turn, suggests a modulatory effect on A2aR whereby a given oligomerization profile favors the dynamic formation of specific supramolecular signaling complexes.

Thermodynamics and Kinetics of Aggregation of Flexible Peripheral Membrane Proteins

Biomembrane remodeling is essential for cellular trafficking, with membrane-binding peripheral proteins playing a key role in it. Significant membrane remodeling as in endo- and exocytosis is often due to aggregates of many proteins with direct or membrane-mediated interactions. Understanding this process via computer simulations is extremely challenging: protein-membrane systems involve time and length scales that make atomistic simulations impractical, while most coarse-grained models fall short in resolving dynamics and physical effects of protein and membrane flexibility. Here, we develop a coarse-grained model of the bilayer membrane bestrewed with rotationally symmetric flexible proteins, parametrized to reflect local curvatures and lateral dynamics of proteins. We investigate the kinetics, equilibrium distributions, and the free energy landscape governing the formation and breakup of protein clusters on the surface of the membrane. We demonstrate how the flexibility of the proteins as well as their surface concentration play deciding roles in highly selective macroscopic aggregation behavior.

Mechanistic Understanding from Molecular Dynamics in Pharmaceutical Research 2: Lipid Membrane in Drug Design

We review the use of molecular dynamics (MD) simulation as a drug design tool in the context of the role that the lipid membrane can play in drug action, i.e., the interaction between candidate drug molecules and lipid membranes. In the standard "lock and key" paradigm, only the interaction between the drug and a specific active site of a specific protein is considered; the environment in which the drug acts is, from a biophysical perspective, far more complex than this. The possible mechanisms though which a drug can be designed to tinker with physiological processes are significantly broader than merely fitting to a single active site of a single protein. In this paper, we focus on the role of the lipid membrane, arguably the most important element outside the proteins themselves, as a case study. We discuss work that has been carried out, using MD simulation, concerning the transfection of drugs through membranes that act as biological barriers in the path of the drugs, the behavior of drug molecules within membranes, how their collective behavior can affect the structure and properties of the membrane and, finally, the role lipid membranes, to which the vast majority of drug target proteins are associated, can play in mediating the interaction between drug and target protein. This review paper is the second in a two-part series covering MD simulation as a tool in pharmaceutical research; both are designed as pedagogical review papers aimed at both pharmaceutical scientists interested in exploring how the tool of MD simulation can be applied to their research and computational scientists interested in exploring the possibility of a pharmaceutical context for their research.

Structural variability and concerted motions of the T cell receptor - CD3 complex

We investigate the structural and orientational variability of the membrane-embedded T cell receptor (TCR) – CD3 complex in extensive atomistic molecular dynamics simulations based on the recent cryo-EM structure determined by Dong et al., 2019. We find that the TCR extracellular (EC) domain is highly variable in its orientation by attaining tilt angles relative to the membrane normal that range from 15° to 55°. The tilt angle of the TCR EC domain is both coupled to a rotation of the domain and to characteristic changes throughout the TCR – CD3 complex, in particular in the EC interactions of the Cβ FG loop of the TCR, as well as in the orientation of transmembrane helices. The concerted motions of the membrane-embedded TCR – CD3 complex revealed in our simulations provide atomistic insights on conformational changes of the complex in response to tilt-inducing forces on antigen-bound TCRs.

Cholesterol plays a decisive role in tetraspanin assemblies during bilayer deformations

The tetraspanin family plays key roles in many physiological processes, such as, tumour invasion, cell motility, virus infection, cell attachment and entry. Tetraspanins function as molecular scaffolds organized in microdomains with interesting downstream cellular consequences. However, despite their relevance in human physiology, the precise mechanisms of their various functions remain elusive. In particular, the full-length CD81 tetraspanin has interesting cholesterol-related properties that modulate its activity in cells. In this work, we study the opening transition of CD81 under different conditions. We propose that such conformational change is a collaborative process enhanced by simultaneous interactions between multiple identical CD81 tetraspanins. With molecular dynamics simulations we describe the crucial role of a ternary lipid bilayer with cholesterol in CD81 conformational dynamics, observing two emergent properties: first, clusters of CD81 collectively segregate one tetraspanin while favouring one opening transition, second, cumulative cholesterol sequestering by CD81 tetraspanins inhibits large membrane deformations due to local density variations.

Structural and Functional Insights into the Transmembrane Domain Association of Eph Receptors

Eph receptors are the largest family of receptor tyrosine kinases and by interactions with ephrin ligands mediate a myriad of processes from embryonic development to adult tissue homeostasis. The interaction of Eph receptors, especially at their transmembrane (TM) domains is key to understanding their mechanism of signal transduction across cellular membranes. We review the structural and functional aspects of EphA1/A2 association and the techniques used to investigate their TM domains: NMR, molecular modelling/dynamics simulations and fluorescence. We also introduce transmembrane peptides, which can be used to alter Eph receptor signaling and we provide a perspective for future studies.

Development of Martini 2.2 parameters for N-glycans: a case study of the HIV-1 Env glycoprotein dynamics

N-linked glycans are ubiquitous in nature and play key roles in biology. For example, glycosylation of pathogenic proteins is a common immune evasive mechanism, hampering the development of successful vaccines. Due to their chemical variability and complex dynamics, an accurate molecular understanding of glycans is still limited by the lack of effective resolution of current experimental approaches. Here, we have developed and implemented a reductive model based on the popular Martini 2.2 coarse-grained force field for the computational study of N-glycosylation. We used the HIV-1 Env as a direct applied example of a highly glycosylated protein. Our results indicate that the model not only reproduces many observables in very good agreement with a fully atomistic force field but also can be extended to study large amount of glycosylation variants, a fundamental property that can aid in the development of drugs and vaccines.